Senior ML Engineer – AI Research, Portability

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Create and construct research prototypes and resilient systems at the intersections of models, providers, and agent runtimes.

• Develop research inquiries and establish evaluation methodologies.

• Experiment with concepts in realistic agent workflows and transform promising outcomes into reusable components.

• Design, implement, train, and assess model routers.

• Create portable provider and protocol abstractions that maintain authentication, telemetry, cache and context signals, and execution provenance.

• Specify versioned schemas and contracts for models, providers, agents, workspaces, skills, actions, tools, memories, and trajectories.

• Construct systems that identify, package, adapt, and validate agent skills across coding agents, editors, and other harnesses.

• Investigate user-owned memory, scoped identity, trajectory checkpoints, terminal outcomes, retrieval quality, and reviewable context compaction.

• Develop benchmark suites and evaluation protocols for quality, cost, latency, reliability, safety, and portability.

• Design evaluations for held-out, out-of-domain, and change impacts.

• Explore distillation, self-improving harnesses, multi-agent training, agent factories, and automated skill creation.

• Produce robust research software, APIs, integration layers, and testing infrastructure.

• Collaborate across research, infrastructure, security, product, and engineering teams.

• Present findings through technical reports, demonstrations, open-source releases, benchmarks, and research publications.

⛳️ Requirements

• A deep understanding of machine learning, large language models, or statistical decision-making.

• Extensive expertise in at least one pertinent area, such as model routing, recommender systems, agent systems, retrieval and memory, model evaluation, distributed systems, or protocol and API design.

• Experience in constructing and evaluating modern language-model or agent systems, including tool utilization and multi-turn workflows.

• Experience in designing, executing, and analyzing machine learning experiments with suitable statistical rigor.

• Ability to articulate meaningful research questions, design experiments that test well-defined hypotheses, and derive defensible conclusions.

• Knowledge of evaluation leakage, held-out testing, out-of-domain generalization, uncertainty, and reproducibility.

• Strong software engineering and algorithm design capabilities; excellent Python skills and proficiency in production systems.

• Experience with APIs, data schemas, distributed services, testing, observability, code review, and CI/CD.

• Ability to consider security, privacy, provenance, permissions, failure modes, and user control in agent systems.

• Experience in implementing research concepts and rapidly iterating through modeling, data, systems, and evaluation.

• Strong communication and technical leadership skills, including collaboration across research and engineering fields and clear documentation of insights in technical reports or research publications.

• Excellent command of English, with strong technical writing, presentation, and communication skills.

• Applicants must be authorized to work in the country where they apply and provide proof of employment eligibility as a condition of hire.

🏝️ Benefits

• Competitive compensation.

• Opportunities for career advancement and learning.

• Flexibility and autonomy.

• A collaborative and innovative culture.

• Chance to work on impactful AI projects.

• An international environment with talented teams.

• Fast-paced work environment.

• Encouragement of bold thinking.

• Continuous growth opportunities.

• Meaningful impact.

• Trust and genuine ownership.

• Opportunity to influence the future of AI.

• Equal employment opportunities.

• Accommodations available during the application process.